Dynamic optimization of conditional models with application to chemical process operation and design

条件模型可以定义为系统方程取决于模型解所在位置的模型。在动态环境中，系统可以在不同的模式下运行，模式之间的转换由离散事件触发。这种类型的化工过程系统的例子很常见，包括可能溢出或干涸的容器，多相系统中的一个相的出现或消失，以及执行器饱和。不连续行为也可能由控制系统，如基于逻辑的监控控制器引起。本研究方案解决了条件动态模型的优化问题，主要关注由控制系统引起模型不连续的情况。需要考虑的应用包括调节和监督控制系统设计、过渡系统的优化和动态可操作对象的优化设计。本研究的广泛目标是为这类问题开发有效的表述和解决策略，表征特定问题类的收敛性质，并开发与工业相关的新应用。条件模型的动态优化最近才在过程系统社区内受到关注。希望通过这项研究，在具有工业意义的新颖设计和控制应用中开发可靠和有效的技术来解决这类问题。

Conditional models may be defined as those in which the system equations depend on where the model solution lies.  In a dynamic setting, the system could operate in different modes, with the transition between modes triggered by discrete events.  Examples of chemical process systems that exhibit behavior of this type are commonplace, and include vessels that could overflow or run dry, appearance or disappearance of a phase in a multiphase system, and actuator saturation.  Discontinuous behavior may also be induced by control systems such as logic-based supervisory controllers.  This research proposal addresses the optimization of conditional dynamic models, focusing primarily on situations in which the model discontinuities are induced by control systems.  Applications to be considered include regulatory and supervisory control system design, optimization of systems in transition, and optimal design of dynamically operable plants.  The broad goals of this research are to develop effective formulation and solution strategies for such problems, characterize the convergence properties for specific problem classes, and develop novel applications of industrial relevance.  Dynamic optimization of conditional models has only recently received attention within the process systems community.  It is hoped that through this research, reliable and efficient techniques will be developed for the solution of such problems in novel design and control applications of industrial significance.